Abstract
As discussed in Chapters 1 and 2, IVSs employ a sequence of image understanding algorithms in which the output of an algorithm is the input of the next algorithm in the sequence. Algorithms that constitute an integrated vision systems exhibit different characteristics, and therefore, require different data decomposition techniques and efficient load balancing techniques for parallel implementation. Since the input data of a task is produced as the output data of the previous task, this information can be exploited to perform knowledge based data decomposition and load balancing.
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© 1990 Kluwer Academic Publishers
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Choudhary, A.N., Patel, J.H. (1990). Load Balancing and Scheduling Techniques. In: Parallel Architectures and Parallel Algorithms for Integrated Vision Systems. The Kluwer International Series in Engineering and Computer Science, vol 108. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1539-1_6
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DOI: https://doi.org/10.1007/978-1-4613-1539-1_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4612-8825-1
Online ISBN: 978-1-4613-1539-1
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